CN113037822A - Media data platform based on wireless network and cloud computing - Google Patents
Media data platform based on wireless network and cloud computing Download PDFInfo
- Publication number
- CN113037822A CN113037822A CN202110227072.XA CN202110227072A CN113037822A CN 113037822 A CN113037822 A CN 113037822A CN 202110227072 A CN202110227072 A CN 202110227072A CN 113037822 A CN113037822 A CN 113037822A
- Authority
- CN
- China
- Prior art keywords
- audio
- result
- user
- module
- media data
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Images
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/50—Network services
- H04L67/55—Push-based network services
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/10—Protocols in which an application is distributed across nodes in the network
Landscapes
- Engineering & Computer Science (AREA)
- Computer Networks & Wireless Communication (AREA)
- Signal Processing (AREA)
- Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
Abstract
The invention relates to a media data platform based on a wireless network and cloud computing, which comprises a user interaction module, a data processing module and a data processing module, wherein the user interaction module is used for interacting with a terminal held by a user, acquiring an interaction request from the terminal and feeding back an interaction result; the user portrait processing module is used for processing data related to a user to obtain a first result, and feeding the first result back to the scene information processing module and the cloud computing module; the scene information processing module is used for processing data related to a scene to obtain a second result, and feeding the second result back to the cloud computing module; the cloud computing module is used for processing media data according to the first result and the second result to obtain a media data processing result, feeding the media data processing result back to the user interaction module, and the user interaction module generates feedback information according to the media data processing result and sends the feedback information to a terminal held by the user. The invention can provide interactive media data service for large data volume users concurrently.
Description
Technical Field
The invention relates to the field of internet communication, in particular to a media data platform based on a wireless network and cloud computing.
Background
With the development of internet technology, cloud computing is increasingly becoming an important way for internet enterprises to improve computing power optimization services, and by means of cloud computing, a corresponding data processing method is designed in big data, and a media data platform is built, so that resources can be better integrated, and the purpose of external quick service is achieved.
Disclosure of Invention
The technical scheme of the invention is as follows:
a media data platform based on wireless network and cloud computing comprises:
the user interaction module is used for interacting with a terminal held by a user, acquiring an interaction request from the terminal and feeding back an interaction result;
the user portrait processing module is used for processing data related to a user to obtain a first result, and feeding the first result back to the scene information processing module and the cloud computing module;
the scene information processing module is used for processing data related to a scene to obtain a second result, and feeding the second result back to the cloud computing module;
the cloud computing module is used for processing media data according to the first result and the second result to obtain a media data processing result, feeding the media data processing result back to the user interaction module, and the user interaction module generates feedback information according to the media data processing result and sends the feedback information to a terminal held by the user.
Preferably, the media data platform further comprises:
and the media data warehouse is used for storing mass media data resources, and the media data warehouse can store video resources, audio resources and picture resources.
Preferably, the user interaction module is further configured to obtain an audio recommendation request from a user terminal, where the audio recommendation request includes a user identifier, an audio request source, and an audio optimization recommendation condition;
the user interaction module is further configured to transmit the user identifier to the user portrait processing module to obtain a first result, and the user portrait processing module is configured to transmit the first result to the cloud computing module and the scene information processing module;
the user interaction module is further configured to send the audio request to the scene information processing module to obtain a second result, and the scene information processing module is further configured to transmit the second result to the cloud computing module;
the user interaction module is further used for transmitting the audio request source and the audio optimization recommendation condition to the cloud computing module, and the cloud computing module is used for generating feedback information according to the first result, the second result, the audio request source and the audio optimization recommendation condition;
the cloud computing module is used for transmitting the feedback information to the user interaction module;
the user interaction module is further configured to query the media data warehouse according to the feedback information, generate an interaction result according to the query result, and feed back the interaction result to the user terminal.
Preferably, the interactive request includes an audio query request, an audio upload request, a user right management request, and an audio recommendation request.
An audio recommendation method implemented by the media data platform comprises the following steps:
the user interaction module acquires an audio recommendation request from a user terminal, wherein the audio recommendation request comprises a user identifier, an audio request source and an audio optimization recommendation condition;
the user interaction module transmits the user identification to the user portrait processing module to obtain a first result, and the user portrait processing module transmits the first result to the cloud computing module and the scene information processing module;
the user interaction module sends the audio request to the scene information processing module to obtain a second result, and the scene information processing module transmits the second result to the cloud computing module;
the user interaction module transmits the audio request source and the audio optimization recommendation condition to the cloud computing module, and the cloud computing module generates feedback information according to the first result, the second result, the audio request source and the audio optimization recommendation condition;
the cloud computing module transmits the feedback information to the user interaction module;
and the user interaction module queries the media data warehouse according to the feedback information, generates an interaction result according to the query result, and feeds the interaction result back to the user terminal.
An electronic device, comprising:
a processor;
a memory for storing the processor-executable instructions;
wherein the processor is configured to execute the instructions to implement the audio recommendation method described above.
A computer-readable storage medium, wherein instructions, when executed by a processor of an electronic device, enable the electronic device to perform the above-described audio recommendation method.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the invention, as claimed.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and together with the description, serve to explain the principles of the invention and are not to be construed as limiting the invention.
FIG. 1 is a schematic diagram illustrating a wireless network and cloud computing based media data platform in accordance with an exemplary embodiment;
FIG. 2 is a flowchart illustrating a method of audio recommendation, according to an example embodiment;
FIG. 3 is a schematic flow chart illustrating the generation of feedback information based on the first result, the second result, the source of the audio request, and the audio optimization recommendation, according to an example embodiment;
FIG. 4 is a block diagram illustrating an electronic device associating database queries in accordance with an exemplary embodiment.
Detailed Description
In order to make those skilled in the art better understand the technical solution of the present invention, the technical solution in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings.
It should be noted that the terms first, second and the like in the description and in the claims of the present invention and in the drawings described above are used for distinguishing between similar entities and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the invention described herein are capable of operation in sequences other than those illustrated or described herein. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present invention. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the invention, as detailed in the appended claims.
The embodiment of the invention shows a media data platform based on a wireless network and cloud computing, as shown in fig. 1, the media data platform comprises:
and the user interaction module 10 is used for interacting with a terminal held by a user, acquiring an interaction request from the terminal and feeding back an interaction result.
And the user portrait processing module 20 is used for processing data related to the user to obtain a first result, and feeding the first result back to the scene information processing module and the cloud computing module.
And the scene information processing module 30 is configured to process data related to a scene to obtain a second result, and feed the second result back to the cloud computing module.
The cloud computing module 40 is configured to perform media data processing according to the first result and the second result to obtain a media data processing result, and feed back the media data processing result to the user interaction module, where the user interaction module generates feedback information according to the media data processing result.
A media data repository 50 for storing mass media data assets. Illustratively, the media data repository may store video assets, audio assets, and picture assets.
Taking the interaction request as an audio recommendation request as an example, the terminal held by the user sends the audio recommendation request to the media data platform, and the feedback information finally generated by the cloud computing module may be an identifier of the audio to be recommended. The user interaction module may extract an audio cover of the corresponding audio from the media data repository according to the identifier of the audio to be recommended, and feed back the audio cover as the interaction result to a terminal held by the user.
In one possible embodiment, the interactive request is an audio recommendation request, and the audio recommendation request includes a user identifier, an audio request source, and an audio optimization recommendation condition.
Wherein the request source can be used for describing a corresponding scene when the user triggers the audio recommendation request. For example, the user may trigger the audio recommendation request in different scenes, and accordingly, the audio recommendation request may carry an audio request source, and the audio request source may be an identifier corresponding to the scene. For example, if the scene is an audio original website application, the audio request source may be an identifier corresponding to the audio original website application, and if the scene is a bullet screen website, the audio request source may be an identifier corresponding to the application of the bullet screen website.
The audio frequency optimization recommendation condition can be used for optimizing and recommending audio frequency which meets user requirements in mass audio frequency resources, and the audio frequency recommendation accuracy is improved. Exemplary audio optimization recommendation conditions may include audio playback volume, audio duration, audio author popularity, audio discussion.
The embodiment of the present invention further illustrates a method for the media data platform to perform audio recommendation for a user in response to a user audio recommendation request, where the method is implemented by the media data platform, and as shown in fig. 2, the method includes:
s101, the user interaction module obtains an audio recommendation request from a user terminal, wherein the audio recommendation request comprises a user identification, an audio request source and an audio optimization recommendation condition.
And S102, the user interaction module transmits the user identification to the user portrait processing module to obtain a first result, and the user portrait processing module transmits the first result to the cloud computing module and the scene information processing module.
Specifically, the transmitting the user identifier to the user representation processing module to obtain a first result includes:
and S1021, the user portrait processing module obtains a corresponding user portrait according to the user identification.
The user representation in the embodiment of the present invention is not particularly limited, and may generally refer to information related to the user, such as a user identifier, a user age, a user occupation, a user gender, an audio tag interested by the user, social information of the user, audio observed by the user, audio reviewed by the user, and the like.
And S1022, performing feature extraction on the user portrait to obtain user portrait features corresponding to the user portrait.
The embodiment of the present invention does not limit the specific method for feature extraction, and the prior art may be used.
And S1023, mapping the user portrait characteristics into a first correction factor.
And S1024, taking the user image characteristics and a first correction factor as the first result.
S103, the user interaction module transmits the audio request source to the scene information processing module to obtain a second result, and the scene information processing module transmits the second result to the cloud computing module.
Specifically, the transmitting the audio request source to the scene information processing module obtains a second result:
and S1031, the scene information processing module obtains a corresponding scene identifier according to the audio request source.
S1032, feature extraction is carried out on the scene identification, and the obtained feature extraction result is fused with the user portrait feature in the first result to obtain the scene user portrait feature.
The embodiment of the present invention does not limit the specific method for feature extraction, and the prior art may be used.
S1033, mapping the scene user portrait characteristics to a second correction factor.
Referring to step S1023, further description is omitted here.
S104, the user interaction module transmits the audio request source and the audio optimization recommendation condition to the cloud computing module, and the cloud computing module generates feedback information according to the first result, the second result, the audio request source and the audio optimization recommendation condition.
Specifically, the generating feedback information according to the first result, the second result, the audio request source, and the audio optimization recommendation condition, as shown in fig. 3, includes:
s1041, extracting an alternative audio identification set from the media data warehouse according to the audio request source and the audio optimization recommendation condition.
The media data warehouse can store audio data of various sources, for example, the audio data of a bullet screen website can be stored, the audio data of an audio original website platform can also be stored, and an alternative audio identification set is formed by the identifications of the audio data inquired according to the audio request source and the audio optimization recommendation condition.
Specifically, the extracting, in the media data store, an alternative audio identifier set according to the audio request source and the audio optimization recommendation condition includes:
s10411, obtaining a corresponding initial audio identification set according to the audio request source.
S10412, extracting an optimized recommendation field in the audio optimized recommendation condition, and querying the media data warehouse according to the optimized recommendation field and each audio identifier in the initial audio identifier set to obtain an audio entity corresponding to each audio identifier, so as to form an audio entity set.
Specifically, for each optimized recommendation field, querying the media data repository by using the optimized recommendation field and each audio identifier as query conditions to trigger the media data repository to feed back a query result, where the query result represents a value of the audio corresponding to each audio identifier in the optimized recommendation field. According to the method, query results corresponding to the optimized recommendation fields in the audio optimized recommendation conditions are obtained through query, and a query entity is generated according to the query results, wherein the query entity corresponds to each audio identifier.
Illustratively, the audio identifier 0001, and the optimized recommendation field is audio playback volume, audio duration, audio author popularity, and audio discussion, and it can be known by querying the media data repository that the audio playback volume, audio duration, audio author popularity, and audio discussion of the audio identifier 0001 are 866 ten thousand, 2 minutes, 8964 focus, and 3236 comment number, respectively. Then, according to "866 million, 2 minutes, 8964 attention, 3236 comment number", an audio entity corresponding to the audio identifier 0001 is obtained, and the audio entity has four dimensions of audio playback volume, audio duration, audio author popularity, and audio discussion.
S10413, initializing the first audio entity queue, the candidate audio entity set and the second audio entity queue to be empty sets, and determining the audio entity set as a current audio entity set.
S10414, accessing each audio entity in the current audio entity set, updating the first audio entity queue and the second audio entity queue according to the access result, wherein the audio entities in the first audio entity queue cannot be suppressed by each other, and the audio entities in the second audio entity queue cannot be suppressed by the audio entities in the first audio entity queue.
In the embodiment of the present invention, if and only if the value of any dimension of the audio entity a is greater than or equal to the value of the corresponding dimension of the data audio entity B, and the values of the dimensions of the audio entity a cannot be all equal to the values of the corresponding dimensions of the audio entity B, the audio entity a is said to suppress the audio entity B.
In one embodiment, the accessing each entity in the current audio entity set and updating the first audio entity queue and the second audio entity queue according to the access result includes:
the following operations are sequentially executed for the audio entities in the current audio entity set:
s10, extracting a current audio entity:
s20, if a first audio entity capable of suppressing the current audio entity exists in the first audio entity queue, directly deleting the current audio entity in the current audio entity set;
s30, if a second audio entity capable of being suppressed by the current audio entity exists in the first audio entity queue, deleting the second audio entity from the first audio entity queue, and inserting the current audio entity into the first audio entity queue;
s40, if the current audio entity and all audio entities in the first audio entity queue do not have a suppression relation, judging whether the first audio entity queue has a space capable of storing a new audio entity, if so, inserting the current audio entity into the first audio entity queue, and if not, adding the current audio entity into the second audio entity queue.
S10415, outputting the audio entity in the first audio entity queue to the candidate audio entity set, and emptying the first audio entity queue.
S10416, if the second audio entity queue is not empty, determining the second audio entity queue as the current audio entity set, emptying the second audio entity queue, and returning to execute the step S10414.
S10417, if the second audio entity queue is empty, obtaining a candidate audio identification set according to the identification of the audio entity in the candidate audio entity set.
Compared with the method that before the subsequent recommendation degree calculation, the audio identifiers in the initial audio identifier set are screened according to the recommendation optimization conditions, the video which is comprehensively and best represented in the dimensionality defined by the recommendation optimization conditions can be selected, the candidate audio identifier set is formed, the audio is screened from the perspective of objective comprehensive representation, and the audio data which not only meets the subjective tendency of the user, but also has the objective comprehensive representation in the perspective defined by the recommendation optimization conditions can be recommended for the user by combining the recommendation degree calculation result, so that the comprehensive quality of the recommended audio is improved.
S1042, calculating the recommendation degree of each audio identifier in the alternative audio identifier set.
The embodiment of the invention discloses a method for calculating recommendation degree of a certain audio identifier, which comprises the following steps:
s10421, extracting the characteristics of the audio corresponding to the audio identification to obtain audio characteristics.
S10422, fusing the audio frequency characteristic with the user portrait characteristic in the first result to obtain a basic fusion characteristic.
S10423, multiplying the basic fusion feature, the second correction factor and the first correction factor, and inputting the multiplication result into a recommendation model to obtain the recommendation degree output by the recommendation model.
In the embodiment of the invention, the user portrait characteristics can be obtained based on a first characteristic extraction network, the first correction factor is obtained based on the first mapping network, the service personalized parameter is obtained based on a second mapping network, the audio characteristics are obtained based on the second characteristic extraction network, the recommendation degree is calculated based on a recommendation model, and the first characteristic extraction network, the first mapping network, the second characteristic extraction network and the recommendation model are adjusted in a feedback mode according to loss in the training process.
Compared with the recommendation model in the related technology, the recommendation calculation method and the recommendation calculation system can obtain a more accurate recommendation calculation result, and accordingly, a media data platform can feed back a more accurate interaction result.
S1043, taking the audio frequency identification with the recommendation degree larger than a preset threshold value as a target audio frequency identification, and taking the target audio frequency identification as the feedback information.
And S105, the cloud computing module transmits the feedback information to the user interaction module.
And S106, the user interaction module queries the media data warehouse according to the feedback information, generates an interaction result according to the query result, and feeds the interaction result back to the user terminal.
In other possible embodiments, the media data platform may also respond to other interaction requests of the user and correspondingly feed back an interaction result, for example, the interaction request may be an audio query request, an audio upload request, or a user right management request, which is not limited in this embodiment of the present invention.
The media data platform in the embodiment of the invention can provide interactive media data service for a large data volume user concurrently, obtain the interactive request of the user, feed back the interactive result adaptively, and ensure the high accuracy of the interactive structure.
In the embodiment of the present invention, each logic component of the media data platform may perform the following actions:
the user interaction module is further used for acquiring an audio recommendation request from a user terminal, wherein the audio recommendation request comprises a user identifier, an audio request source and an audio optimization recommendation condition;
the user interaction module is further configured to transmit the user identifier to the user portrait processing module to obtain a first result, and the user portrait processing module is configured to transmit the first result to the cloud computing module and the scene information processing module;
the user interaction module is further configured to send the audio request to the scene information processing module to obtain a second result, and the scene information processing module is further configured to transmit the second result to the cloud computing module;
the user interaction module is further used for transmitting the audio request source and the audio optimization recommendation condition to the cloud computing module, and the cloud computing module is used for generating feedback information according to the first result, the second result, the audio request source and the audio optimization recommendation condition;
the cloud computing module is used for transmitting the feedback information to the user interaction module;
the user interaction module is further configured to query the media data warehouse according to the feedback information, generate an interaction result according to the query result, and feed back the interaction result to the user terminal.
In an exemplary embodiment, there is also provided an electronic device, comprising a processor; a memory for storing processor-executable instructions; wherein the processor is configured to carry out the steps of the audio recommendation method provided in any of the above embodiments when executing the instructions stored in the memory.
The electronic device may be a terminal, a server, or a similar computing device, taking the electronic device as a server as an example, fig. 4 is a block diagram of an electronic device for executing the audio recommendation method according to an exemplary embodiment, where the electronic device 1000 may have a relatively large difference due to different configurations or performances, and may include one or more Central Processing Units (CPUs) 1010 (the processor 1010 may include but is not limited to a Processing device such as a microprocessor MCU or a programmable logic device FPGA), a memory 1030 for storing data, and one or more storage media 1020 (e.g., one or more mass storage devices) for storing an application 1023 or data 1022. Memory 1030 and storage media 1020 may be, among other things, transient or persistent storage. The program stored in the storage medium 1020 may include one or more modules, each of which may include a sequence of instructions operating on an electronic device. Still further, the central processor 1010 may be configured to communicate with the storage medium 1020 to execute a series of instruction operations in the storage medium 1020 on the electronic device 1000. The electronic device 1000 may also include one or more power supplies 1060, one or more wired or wireless network interfaces 1050, one or more input-output interfaces 1040, and/or one or more operating systems 1021, such as Windows Server, Mac OS XTM, UnixTM, LinuxTM, FreeBSDTM, and so forth.
Input-output interface 1040 may be used to receive or transmit data via a network. Specific examples of the network described above may include a wireless network provided by a communication provider of the electronic device 1000. In one example, i/o Interface 1040 includes a Network adapter (NIC) that may be coupled to other Network devices via a base station to communicate with the internet. In an exemplary embodiment, the input/output interface 100 may be a Radio Frequency (RF) module, which is used for communicating with the internet in a wireless manner.
It will be understood by those skilled in the art that the structure shown in fig. 4 is only an illustration and is not intended to limit the structure of the electronic device. For example, the electronic device 1000 may also include more or fewer components than shown in FIG. 4, or have a different configuration than shown in FIG. 4.
In an exemplary embodiment, a computer-readable storage medium is also provided, in which instructions, when executed by a processor of an electronic device, enable the electronic device to perform the steps of any of the audio recommendation methods of the above embodiments.
In an exemplary embodiment, a computer program product is also provided that includes computer instructions stored in a computer readable storage medium. The processor of the electronic device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the electronic device executes the audio recommendation method provided in any one of the above embodiments.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in the embodiments provided herein may include non-volatile and/or volatile memory, among others. Non-volatile memory can include read-only memory (ROM), Programmable ROM (PROM), Electrically Programmable ROM (EPROM), Electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDRSDRAM), Enhanced SDRAM (ESDRAM), Synchronous Link DRAM (SLDRAM), Rambus Direct RAM (RDRAM), direct bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).
Other embodiments of the invention will be apparent to those skilled in the art from consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of the invention following, in general, the principles of the invention and including such departures from the present disclosure as come within known or customary practice within the art to which the invention pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the invention being indicated by the following claims.
It will be understood that the invention is not limited to the precise arrangements described above and shown in the drawings and that various modifications and changes may be made without departing from the scope thereof. The scope of the invention is limited only by the appended claims.
Claims (7)
1. Media data platform based on wireless network and cloud computing, characterized by comprising:
the user interaction module is used for interacting with a terminal held by a user, acquiring an interaction request from the terminal and feeding back an interaction result;
the user portrait processing module is used for processing data related to a user to obtain a first result, and feeding the first result back to the scene information processing module and the cloud computing module;
the scene information processing module is used for processing data related to a scene to obtain a second result, and feeding the second result back to the cloud computing module;
the cloud computing module is used for processing media data according to the first result and the second result to obtain a media data processing result, feeding the media data processing result back to the user interaction module, and the user interaction module generates feedback information according to the media data processing result.
2. The media data platform of claim 1, further comprising:
and the media data warehouse is used for storing mass media data resources, and the media data warehouse can store video resources, audio resources and picture resources.
3. The media data platform of claim 2, wherein:
the user interaction module is further used for acquiring an audio recommendation request from a user terminal, wherein the audio recommendation request comprises a user identifier, an audio request source and an audio optimization recommendation condition;
the user interaction module is further configured to transmit the user identifier to the user portrait processing module to obtain a first result, and the user portrait processing module is configured to transmit the first result to the cloud computing module and the scene information processing module;
the user interaction module is further configured to send the audio request to the scene information processing module to obtain a second result, and the scene information processing module is further configured to transmit the second result to the cloud computing module;
the user interaction module is further used for transmitting the audio request source and the audio optimization recommendation condition to the cloud computing module, and the cloud computing module is used for generating feedback information according to the first result, the second result, the audio request source and the audio optimization recommendation condition;
the cloud computing module is used for transmitting the feedback information to the user interaction module;
the user interaction module is further configured to query the media data warehouse according to the feedback information, generate an interaction result according to the query result, and feed back the interaction result to the user terminal.
4. The media data platform of any of claims 1-3, wherein the interaction request comprises an audio query request, an audio upload request, a user rights management request, and an audio recommendation request.
5. An audio recommendation method implemented by the media data platform of any of claims 1-4, the method comprising:
the user interaction module acquires an audio recommendation request from a user terminal, wherein the audio recommendation request comprises a user identifier, an audio request source and an audio optimization recommendation condition;
the user interaction module transmits the user identification to the user portrait processing module to obtain a first result, and the user portrait processing module transmits the first result to the cloud computing module and the scene information processing module;
the user interaction module sends the audio request to the scene information processing module to obtain a second result, and the scene information processing module transmits the second result to the cloud computing module;
the user interaction module transmits the audio request source and the audio optimization recommendation condition to the cloud computing module, and the cloud computing module generates feedback information according to the first result, the second result, the audio request source and the audio optimization recommendation condition;
the cloud computing module transmits the feedback information to the user interaction module;
and the user interaction module queries the media data warehouse according to the feedback information, generates an interaction result according to the query result, and feeds the interaction result back to the user terminal.
6. An electronic device, comprising:
a processor;
a memory for storing the processor-executable instructions;
wherein the processor is configured to execute the instructions to implement the audio recommendation method of any of claim 5.
7. A computer-readable storage medium whose instructions, when executed by a processor of an electronic device, enable the electronic device to perform the audio recommendation method of any of claim 5.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110227072.XA CN113037822B (en) | 2021-03-01 | 2021-03-01 | Media data platform based on wireless network and cloud computing |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110227072.XA CN113037822B (en) | 2021-03-01 | 2021-03-01 | Media data platform based on wireless network and cloud computing |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN113037822A true CN113037822A (en) | 2021-06-25 |
| CN113037822B CN113037822B (en) | 2022-05-03 |
Family
ID=76465122
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110227072.XA Active CN113037822B (en) | 2021-03-01 | 2021-03-01 | Media data platform based on wireless network and cloud computing |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113037822B (en) |
Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106981029A (en) * | 2016-01-15 | 2017-07-25 | 林慧隆 | Based on supply and demand Candidate Recommendation to develop the System and method for of the interpersonal social networks of depth |
| CN107229708A (en) * | 2017-05-27 | 2017-10-03 | 科技谷（厦门）信息技术有限公司 | A kind of personalized trip service big data application system and method |
| US20170324807A1 (en) * | 2016-05-05 | 2017-11-09 | International Business Machines Corporation | Proactive content push for enhancing real-time service delivery via cloud |
| CN107688952A (en) * | 2016-08-04 | 2018-02-13 | 湖南移商动力网络技术有限公司 | A kind of e-commerce user behavioral data analytical technology of cloud computing |
| CN108076439A (en) * | 2016-11-18 | 2018-05-25 | 上海掌门科技有限公司 | For the method and apparatus based on wireless access point PUSH message |
| CN109740068A (en) * | 2019-01-29 | 2019-05-10 | 腾讯科技（北京）有限公司 | Media data recommended method, device and storage medium |
| CN111177563A (en) * | 2019-12-31 | 2020-05-19 | 北京顺丰同城科技有限公司 | Information recommendation method and device, electronic equipment and storage medium |
| CN111310038A (en) * | 2020-02-06 | 2020-06-19 | 腾讯科技（深圳）有限公司 | Information recommendation method and device, electronic equipment and computer-readable storage medium |
| CN111372192A (en) * | 2020-02-26 | 2020-07-03 | Oppo广东移动通信有限公司 | Information recommendation method and device, terminal and storage medium |
| CN111680221A (en) * | 2020-08-11 | 2020-09-18 | 腾讯科技（深圳）有限公司 | Information recommendation method, device, equipment and computer readable storage medium |
| CN111708950A (en) * | 2020-06-22 | 2020-09-25 | 腾讯科技（深圳）有限公司 | Content recommendation method and device and electronic equipment |
| CN111953763A (en) * | 2020-08-06 | 2020-11-17 | 腾讯科技（深圳）有限公司 | Business data pushing method and device and storage medium |
-
2021
- 2021-03-01 CN CN202110227072.XA patent/CN113037822B/en active Active
Patent Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106981029A (en) * | 2016-01-15 | 2017-07-25 | 林慧隆 | Based on supply and demand Candidate Recommendation to develop the System and method for of the interpersonal social networks of depth |
| US20170324807A1 (en) * | 2016-05-05 | 2017-11-09 | International Business Machines Corporation | Proactive content push for enhancing real-time service delivery via cloud |
| CN107688952A (en) * | 2016-08-04 | 2018-02-13 | 湖南移商动力网络技术有限公司 | A kind of e-commerce user behavioral data analytical technology of cloud computing |
| CN108076439A (en) * | 2016-11-18 | 2018-05-25 | 上海掌门科技有限公司 | For the method and apparatus based on wireless access point PUSH message |
| CN107229708A (en) * | 2017-05-27 | 2017-10-03 | 科技谷（厦门）信息技术有限公司 | A kind of personalized trip service big data application system and method |
| CN109740068A (en) * | 2019-01-29 | 2019-05-10 | 腾讯科技（北京）有限公司 | Media data recommended method, device and storage medium |
| CN111177563A (en) * | 2019-12-31 | 2020-05-19 | 北京顺丰同城科技有限公司 | Information recommendation method and device, electronic equipment and storage medium |
| CN111310038A (en) * | 2020-02-06 | 2020-06-19 | 腾讯科技（深圳）有限公司 | Information recommendation method and device, electronic equipment and computer-readable storage medium |
| CN111372192A (en) * | 2020-02-26 | 2020-07-03 | Oppo广东移动通信有限公司 | Information recommendation method and device, terminal and storage medium |
| CN111708950A (en) * | 2020-06-22 | 2020-09-25 | 腾讯科技（深圳）有限公司 | Content recommendation method and device and electronic equipment |
| CN111953763A (en) * | 2020-08-06 | 2020-11-17 | 腾讯科技（深圳）有限公司 | Business data pushing method and device and storage medium |
| CN111680221A (en) * | 2020-08-11 | 2020-09-18 | 腾讯科技（深圳）有限公司 | Information recommendation method, device, equipment and computer readable storage medium |
Also Published As
| Publication number | Publication date |
|---|---|
| CN113037822B (en) | 2022-05-03 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US11394805B1 (en) | Automatic discovery of API information | |
| CN110321422B (en) | Method for training model on line, pushing method, device and equipment | |
| US10839038B2 (en) | Generating configuration information for obtaining web resources | |
| US20200057958A1 (en) | Identification and application of hyperparameters for machine learning | |
| CN110557284B (en) | Data aggregation method and device based on client gateway | |
| CN108989397B (en) | Data recommendation method and device and storage medium | |
| CN111163072B (en) | Method and device for determining characteristic value in machine learning model and electronic equipment | |
| CN112104505B (en) | Application recommendation method, device, server and computer readable storage medium | |
| CN113364853A (en) | Business service system, business request method and gateway equipment | |
| CN110880100A (en) | Business approval processing method, device and system | |
| CN109753424B (en) | AB test method and device | |
| CN111680799A (en) | Method and apparatus for processing model parameters | |
| CN111026912B (en) | IPTV-based collaborative recommendation method, device, computer equipment and storage medium | |
| CN110781139A (en) | Teaching plan resource management system and method and electronic equipment | |
| CN113037822B (en) | Media data platform based on wireless network and cloud computing | |
| CN111026972B (en) | Subscription data pushing method, device, equipment and storage medium in Internet of things | |
| CN114491093B (en) | Multimedia resource recommendation and object representation network generation method and device | |
| CN115756821A (en) | Online task processing model training and task processing method and device | |
| CN106301906B (en) | Object configuration method and device based on distributed system | |
| CN111597444B (en) | Searching method, searching device, server and storage medium | |
| CN109032747B (en) | Data updating method and device | |
| CN112860955B (en) | Business data management system and method based on cloud computing and big data | |
| CN110716713A (en) | Method for generating project code and computing equipment | |
| CN114968455B (en) | Report generation method and device of application interface and electronic equipment | |
| CN113609332B (en) | Video live broadcast resource recommendation method, system and device |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |